The comorbidity rate of gastroesophageal reflux disease （GERD） and sleep disorders is high， and the two form a vicious circle through the “brain-gut axis”， which seriously impacts the patients’ quality of life. Traditional Chinese medicine （TCM）， guided by the core principles of “holistic concept” and “syndrome differentiation and treatment”， features multi-targeted therapeutic effects with minimal side effects， offering diverse intervention options for clinical practice. From the perspective of the “brain-gut axis”， this article reviews the relationship between the comorbidity of GERD and sleep disorders and systematically examines relevant research findings on how TCM regulates the “brain-gut axis” to intervene in this comorbid condition. The study reveals that the “brain-gut axis” may participate in the pathological progress of GERD accompanied by sleep disorders through pathways such as abnormalities in the secretion of brain-gut peptides （including gastrointestinal secretin）， as well as intestinal dysbiosis. By closely focusing on core pathogenic mechanisms such as “disharmony between the liver and stomach” and “insomnia due to stomach disharmony”， various approaches can be employed， including TCM formulas （e.g.， modified Sini powder combined with Zuojin pills）， external TCM therapies （e.g.， back-shu point digital acupressure）， and integrated traditional Chinese and Western medicine treatments （e.g.， modified Chaihu guizhi ganjiang decoction combined with proton pump inhibitors）. These methods can regulate the levels of neurotransmitters， gastrointestinal hormones， inflammatory factors， and the composition of intestinal microbiota associated with the “brain-gut axis”， thereby achieving simultaneous improvement in both GERD and sleep disorders.

Objective To explore the Diagnosis-Intervention Packet(DIP)group scheme and expense standards of patients with severe respiratory failure,so as to provide decision-making basis for optimizing the group of inten-sive diseases and improving the level of fine management of hospitals.Methods The homepage data of medical re-cords of 299 severe patients mainly diagnosed with respiratory failure from January to September in 2023 from a Grade A general hospital in Yangzhou City was collected,and the influencing factors of total hospitalization expenses were analyzed by single factor analysis and multiple linear regression.The exhaustive chi-square automatic interac-tion detector algorithm for decision tree model was used to establish the case-mix scheme of respiratory failure cases and calculate the expenses of each group.Results Hospitalization day,main surgery/operation,method of leaving hos-pital,and patient outcomes are important classification variables affecting the total inpatient expense of severe respi-ratory failure patients,finally formed 8 DIP groups and corresponding expense standards,with strong inter-group ho-mogeneity and great inter-group heterogeneity.Conclusion The optimizing group scheme of patients with severe re-spiratory failure based on decision tree model is consistent with clinical practice,and expense standard can objective-ly and comprehensively reflect the level of medical resource consumption,meanwhile,it will not greatly increase the burden of expenditure of medical insurance funds.So it can provide reference for the medical insurance government to optimize the group scheme of this disease,and also promote hospitals to improve the level of medical insurance fine management.

Epidural spinal cord stimulation (eSCS) represents an emerging neuromodulation technology that ameliorates motor dysfunction in patients with spinal cord injury, Parkinson's disease, and stroke by activating sensory afferent fibers, enhancing spinal cord neural network integration, optimizing brain-spinal cord information transmission, and inducing neural plasticity. This article reviews the mechanism, electrode implantation, and stimulation parameter of eSCS, and application of eSCS in spinal cord injury, Parkinson's disease, and stroke, aiming to provide valuable insight for its clinical implementation.

Diarrhea-predominant irritable bowel syndrome （IBS-D） is a common digestive system disease with high prevalence and recurrence rates for years， high treatment costs， and serious impacts on patients' quality of life and economic burden. Therefore， it is important to explore new and safe treatment methods. The pathogenesis of IBS-D is complex， in which the gut-brain axis is a key factor. The gut-brain axis， a bidirectional signaling pathway connecting the gastrointestinal tract and the central nervous system， regulates gastrointestinal motility， secretion， and immune responses， playing a key role in the occurrence and development of IBS-D. Up to now， antidiarrheal agents， probiotics， and neurotransmitter modulators are the main methods for the clinical treatment of IBS-D. Although they can partially curb the progression of this disease， the therapeutic effects remain to be improved. Studies have confirmed that traditional Chinese medicine （TCM） has significant advantages in the treatment of IBS-D since it can regulate the gut-brain axis via multiple pathways and targets to improve the gastrointestinal motility and strengthen immune defenses. However， there is a lack of systematic reviews on the regulation of the gut-brain axis by TCM in the treatment of IBS-D. Based on the review of IBS-D-related articles published in recent years， this paper systematically summarized the relationship between the gut-brain axis and IBS-D and the role of TCM in the treatment， providing new ideas for the treatment of IBS-D.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

Objective: To investigate the distribution of HPA, HLA alleles and haplotypes among apheresis platelet donors in Changsha, China, and to establish an apheresis platelet donor database. Methods: High-resolution genotyping of HLA-A and -B was performed using PCR sequence based typing (SBT) and next generation sequencing (NGS). HPA genotyping was conducted using quantitative PCR (Q-PCR). The allele frequency, haplotype frequency and linkage disequilibrium parameters were calculated using the direct counting method, the maximum likelihood method and Arlequin software (V 3.1). Results: A total of 41 HLA-A alleles and 82 HLA-B alleles were detected, and 457 HLA-A-B haplotypes were found, of which 25 showed strong linkage disequilibrium (RLD>0.50). The HPA-3 and HPA-15 had the highest HPA polymorphism and antigen mismatch rate in apheresis platelet donor database in Changsha, and the dual antigen mismatch rate was 0.3704 and 0.3743, respectively. Conclusion: The polymorphism of apheresis platelet donor database in Changsha is complex and has strong regional characteristics. Establishing a high-resolution donor database will strongly support the provision of genetically matched platelets for clinical use, facilitating precise platelet transfusion therapy.

Objective:To explore the clinical application value of artificial intelligence（AI）-assisted training in enhancing the accuracy of nuchal translucency（NT）identification，standardization of measurement，and diagnostic efficacy for abnormalities among ultrasound residents.Methods:A retrospective collection of 300 standard fetal NT ultrasound images was conducted at the Center for Medical Ultrasound，Suzhou Hospital Affiliated of Nanjing Medical University from January 2018 to June 2024. The AI model performed NT measurements and diagnoses once. Four sonographers of different seniority levels（including two resident physicians）independently conducted NT measurements and diagnoses twice. Prior to the experiment，the middle-age and resident sonographers had uniformly completed traditional theory training. Following the first independent measurements，the two resident sonographers received additional AI-assisted training，after which all 4 sonographers performed the second independent measurements. A fetal medicine expert evaluated blindly all the results and compared the differences in NT recognition accuracy，measurement standard rate and diagnosis accuracy between the middle-age sonographer（traditional training only）and two resident sonographers（traditional + AI-assisted training）.Results:For the middle-aged sonographer who only received traditional lecture-based training，the accuracy of NT recognition，standardization rate of measurement，or diagnostic accuracy were not significantly improved befroe and after the training，and the diffrence was not statistically significant（ χ2=0.189，1.887，0.326；all P>0.05）. In contrast，the second-year resident（Resident 2）and first-year resident（Resident 1），who received both traditional lecture-based training and AI training，demonstrated some improvements in the accuracy of NT measurement site recognition，though the differences were not statistically significant（ χ2=1.301，2.418；all P>0.05）. However，both residents did significant improvements in the standardization rate of NT measurement（ χ2=25.768，17.035；all P<0.05）. In terms of diagnostic accuracy，Resident 1 did significant improvement（ χ2=10.180， P<0.05），while Resident 2 also did some improvement，though the difference was not statistically significant（ χ2=2.573， P>0.05）. Conclusions:The AI-assisted training system enhances the ability of ultrasound resident sonographers to recognize，measure，and diagnose NT，providing a novel and efficient training model for standardized residency training in ultrasound specialties.

Objective:To investigate the diagnostic value of fetal cardiac ultrasound view visualization in the first trimester for congenital heart disease（CHD）.Methods:A retrospective analysis was performed on 13 323 singleton fetuses who underwent first-trimester（11-13 +6 weeks）ultrasound screening at the Ultrasound Medicine Center，the Affiliated Suzhou Hospital of Nanjing Medical University from January 2018 to June 2024. Cardiac views including the four-chamber view（4CV），left ventricular outflow tract view（LVOT），and Results:The study group showed significantly higher rates of "poorly visualized" 4CV，LVOT，and 3VT than the control group（2.70% vs. 0.14%， P=0.005；36.49% vs. 4.76%， P<0.001；36.49% vs.2.46%， P<0.001）. The efficacies of combination 1（any view abnormal）and combination 2（any view "poorly visualized" or "abnormal"）were comparable，with AUCs of 0.86 and 0.85（ P=0.424）. The AUCs of combination 3（3VT "poorly visualized" or any view "abnormal"）and combination 4（4CV "poorly visualized" or any view "abnormal"）were 0.88 and 0.86（ P=0.424），all significantly higher than combination 5（LVOT "poorly visualized" or any view "abnormal"，AUC=0.84，all P<0.05）. Conclusions:"Poorly visualized" cardiac views in the first trimester demonstrate good diagnostic efficacy for CHD，particularly when 3VT or 4CV are affected，warranting heightened clinical vigilance for fetal cardiac anomalies.